Research & Knowledge Resources

This mini-review explores the potential role of short peptides, specifically Nano-organo Peptides (NOP) and Mito-organo Peptides (MOP), in enhancing longevity and mitigating age-related decline. These peptides influence key physiological functions, including mitochondrial function, proteostasis, cellular senescence, immunogenicity, and metabolic regulation. Emerging research suggests their application in regenerative medicine and aging therapeutics.

This comprehensive review explores the integration of multiple omics approaches (genomics, transcriptomics, proteomics, metabolomics) in drug discovery, discussing key experimental design considerations, challenges in data integration, and emerging computational solutions for analyzing complex molecular datasets to enhance drug development efficiency.

GATC demonstrates alignment with FDA as it considers the use of artificial intelligence to support regulatory decision-making for drug and biological products.

This review examines the potential of autologous bone marrow-derived mononuclear cell transplantation for treating diabetes, exploring its safety and efficacy compared to traditional treatments. The paper analyzes clinical data on using differentiated stem cells for both Type 1 and Type 2 diabetes patients.

The paper explores innovative AI-based approaches to PTSD treatment using GATC Health's Multiomics Advanced Technology (MAT) platform. The research combines genomics, machine learning, and deep learning to identify biomarkers and develop targeted therapeutics, offering a breakthrough in personalized PTSD treatment and prevention strategies for affected populations, particularly military veterans.

The paper examines how machine learning and AI technologies are transforming preclinical drug discovery, highlighting GATC Health's phenotypic drug discovery pipeline that combines deep learning with systems biology approaches to improve drug development efficiency.

The paper evaluates GATC Health's AI platform performance in predicting molecular target activity through blind chemical structure challenges. Using University of California Irvine's validation study, the platform achieved 91% specificity and 86% sensitivity in screening chemical compounds against biological targets.

Research demonstrates how GATC Health's AI platform identified GATC-021, a novel therapeutic compound that successfully reduced fentanyl intake in preclinical studies. The compound, targeting serotonin receptors, showed effectiveness in both male and female subjects without adverse effects, presenting a promising new approach for treating opioid use disorder.

The research examines how machine learning and AI can enable early prediction of Type 2 Diabetes before clinical symptoms appear. The study explores current challenges in biomarker identification and proposes novel multi-omics approaches combined with AI to enable more accurate disease prognostication.

The paper discusses how AI technology is revolutionizing precision medicine through polypharmacology approaches, showcasing GATC Health's AI platform for developing multi-target drug combinations with improved safety and efficacy for complex conditions.